Bayesian integration of information in hippocampal place cells.

Accurate spatial localization requires a mechanism that corrects for errors, which might arise from inaccurate sensory information or neuronal noise. In this paper, we propose that Hippocampal place cells might implement such an error correction mechanism by integrating different sources of informat...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autores principales: Tamas Madl, Stan Franklin, Ke Chen, Daniela Montaldi, Robert Trappl
Formato: article
Lenguaje:EN
Publicado: Public Library of Science (PLoS) 2014
Materias:
R
Q
Acceso en línea:https://doaj.org/article/c96b3ee0dc614a70a0c9ee01885825cb
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
Descripción
Sumario:Accurate spatial localization requires a mechanism that corrects for errors, which might arise from inaccurate sensory information or neuronal noise. In this paper, we propose that Hippocampal place cells might implement such an error correction mechanism by integrating different sources of information in an approximately Bayes-optimal fashion. We compare the predictions of our model with physiological data from rats. Our results suggest that useful predictions regarding the firing fields of place cells can be made based on a single underlying principle, Bayesian cue integration, and that such predictions are possible using a remarkably small number of model parameters.